A visual information source requires a transmission or a storage medium to convey its message to the observer. The fidelity of transmission and reproduction of the message is closely related to and dependent on the available medium capacity and the manner in which it is used. In the digital world the medium capacity is expressed in bits per second or the bit rate. The transmission of visual information can be improved by compressing the video signal and transmitting the compressed signal. The goal of digital video compression is to represent an image with as low a bit rate as possible, while preserving an appropriate level of picture quality for a given application. Compression is achieved by identifying and removing redundancies.
A bit rate reduction system operates by removing redundant information from the signal at the encoder prior to transmission and re-inserting it at the decoder. An encoder and decoder pair are referred to as a ‘codec’. In video signals, two distinct kinds of redundancy can be identified.                i. Spatial and temporal redundancy where pixel values are not independent, but are correlated with their neighbors both within the same frame and across frames. To some extent, the value of a pixel is predictable given the values of neighboring pixels.        ii. Psycho-visual redundancy where the human eye has a limited response to fine spatial detail and is less sensitive to detail near object edges or around shot-changes. Consequently, controlled impairments introduced into the decoded picture by the bit rate reduction process are not visible to a human observer.        
At its most basic level, compression is performed when an input video stream is analyzed and information that is indiscernible to the viewer is discarded. Each event is then assigned a code where commonly occurring events are assigned fewer bits and rare events are assigned more bits. These steps are commonly referred to as signal analysis, quantization and variable length encoding. Common methods for compression include discrete cosine transform (DCT), vector quantization (VQ), fractal compression, and discrete wavelet transform (DWT).
A video stream can contain text, either as a logo, as subtitles or as a ticker moving across the screen. During compression, images comprising the video stream are quantized by an encoder to lower the bit rate of the video stream. Areas of an image containing text are quantized with the remaining portion of the image. While the reduction in quality of non-textual areas of the video may not be noticeable, lack of clarity in the text areas is noticeable making the text difficult to discern and in some cases render it unreadable.
What is needed is a method to encode a video stream while recognizing text and improving its quality.